Diagnosing breast cancer by using Raman spectroscopy

Haka, Abigail S.; Shafer‐Peltier, Karen; Fitzmaurice, Maryann; Crowe, Joseph P.; Dasari, Ramachandra R.; Feld, Michael S.

doi:10.1073/pnas.0501390102

Cited by 585 publications

(477 citation statements)

References 35 publications

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“…The apparent decrease in triolein as cancer progresses could be due to: (1) the reduction of subcutaneous fat sampled by the probe, caused by the thickening epidermis during lesion formation; and/or (2) the reduction of membrane lipid synthesis induced by UV damage [34]. Because subcutaneous fat exists in a substantial amount and has large Raman scattering cross section [41] we believe (1) is the major reason. The thickening of epidermis originates from the progression of malignancy [42].…”

Section: Discussionmentioning

confidence: 99%

Raman active components of skin cancer

Feng¹,

Moy²,

Nguyen³

et al. 2017

Biomed. Opt. Express

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Raman spectroscopy (RS) has shown great potential in noninvasive cancer screening. Statistically based algorithms, such as principal component analysis, are commonly employed to provide tissue classification; however, they are difficult to relate to the chemical and morphological basis of the spectroscopic features and underlying disease. As a result, we propose the first Raman biophysical model applied to in vivo skin cancer screening data. We expand upon previous models by utilizing in situ skin constituents as the building blocks, and validate the model using previous clinical screening data collected from a Raman optical fiber probe. We built an 830nm confocal Raman microscope integrated with a confocal laser-scanning microscope. Raman imaging was performed on skin sections spanning various disease states, and multivariate curve resolution (MCR) analysis was used to resolve the Raman spectra of individual in situ skin constituents. The basis spectra of the most relevant skin constituents were combined linearly to fit in vivo human skin spectra. Our results suggest collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin and water are the most important model components. We make available for download (see supplemental information) a database of Raman spectra for these eight components for others to use as a reference. Our model reveals the biochemical and structural makeup of normal, nonmelanoma and melanoma skin cancers, and precancers and paves the way for future development of this approach to noninvasive skin cancer diagnosis.

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Section: Discussionmentioning

confidence: 99%

Raman active components of skin cancer

Feng¹,

Moy²,

Nguyen³

et al. 2017

Biomed. Opt. Express

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“…Similar observations were also reported in previous studies using other optical spectroscopy techniques for breast tissue characterization. 44 Haka et al 44 used Raman spectroscopy for the diagnosis of breast cancer, and found that there was increased contribution from collagen in benign and cancerous breast tissues, relative to that in normal breast tissues.…”

Section: Discussionmentioning

confidence: 99%

Diagnosis of breast cancer using fluorescence and diffuse reflectance spectroscopy: a Monte-Carlo-model-based approach

et al. 2008

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We explore the use of Monte-Carlo-model-based approaches for the analysis of fluorescence and diffuse reflectance spectra measured ex vivo from breast tissues. These models are used to extract the absorption, scattering, and fluorescence properties of malignant and nonmalignant tissues and to diagnose breast cancer based on these intrinsic tissue properties. Absorption and scattering properties, including β-carotene concentration, total hemoglobin concentration, hemoglobin saturation, and the mean reduced scattering coefficient are derived from diffuse reflectance spectra using a previously developed Monte Carlo model of diffuse reflectance. A Monte Carlo model of fluorescence described in an earlier manuscript was employed to retrieve the intrinsic fluorescence spectra. The intrinsic fluorescence spectra were decomposed into several contributing components, which we attribute to endogenous fluorophores that may present in breast tissues including collagen, NADH, and retinol/ vitamin A. The model-based approaches removes any dependency on the instrument and probe geometry. The relative fluorescence contributions of individual fluorescing components, as well as β-carotene concentration, hemoglobin saturation, and the mean reduced scattering coefficient display statistically significant differences between malignant and adipose breast tissues. The hemoglobin saturation and the reduced scattering coefficient display statistically significant differences between malignant and fibrous/benign breast tissues. A linear support vector machine classification using (1) fluorescence properties alone, (2) absorption and scattering properties alone, and (3) the combination of all tissue properties achieves comparable classification accuracies of 81 to 84% in sensitivity and 75 to 89% in specificity for discriminating malignant from nonmalignant breast tissues, suggesting each set of tissue properties are diagnostically useful for the discrimination of breast malignancy.

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“…Raman spectroscopy has been proposed as a non-invasive and label free analytical method with a very consistent and prolific track record of in-vitro biomedical applications [22][23][24] for histopathological screening [25][26][27][28][29] as well as probing of lymph node pathology using fibre probes [30][31][32].…”

Section: Introductionmentioning

confidence: 99%

High sensitivity non‐invasive detection of calcifications deep inside biological tissue using Transmission Raman Spectroscopy

Ghiţă

Matousek

Stone

2017

Journal of Biophotonics

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The aim of this research was to develop a novel approach to probe non-invasively the composition of inorganic chemicals buried deep in large volume biological samples. The method is based on advanced Transmission Raman Spectroscopy (TRS) permitting chemical specific detection within a large sampling volume. The approach could be beneficial to chemical identification of the breast calcifications detected during mammographic X-ray procedures. The chemical composition of a breast calcification reflects the pathology of the surrounding tissue, malignant or benign and potentially the grade of malignancy. However, this information is not available from mammography, leading to excisional biopsy and histopathological assessment for a definitive diagnosis. Here we present, for the first time, a design of a new high performance deep Raman instrument and demonstrate its capability to detect type II calcifications (calcium hydroxyapatite) at clinically relevant concentrations and depths of around 40 mm in phantom tissue. This is around double the penetration depth achieved with our previous instrument design and around two orders of magnitude higher than that possible when using conventional Raman spectroscopy.

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Diagnosing breast cancer by using Raman spectroscopy

Cited by 585 publications

References 35 publications

Raman active components of skin cancer

Raman active components of skin cancer

Diagnosis of breast cancer using fluorescence and diffuse reflectance spectroscopy: a Monte-Carlo-model-based approach

High sensitivity non‐invasive detection of calcifications deep inside biological tissue using Transmission Raman Spectroscopy

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